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An algorithm to improve speech recognition in noise for hearing-impaired listeners
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View: Figures


Image of FIG. 1.
FIG. 1.

Schematic diagram of the current speech-segregation system. DNN = deep neural network, IBM = ideal binary mask.

Image of FIG. 2.
FIG. 2.

Segregation of a HINT utterance from speech-shaped noise at −5 dB SNR. (a) Cochleagram of the utterance in quiet. (b) Cochleagram of the speech-plus-noise. (c) IBM. (d) Estimated IBM. (e) Cochleagram of the utterance following noise removal using the estimated IBM.

Image of FIG. 3.
FIG. 3.

Pure-tone air-conduction audiometric thresholds for the listeners with sensorineural hearing impairment. Thresholds in right ears are represented by circles and those in left ears are represented by ×'s. Also displayed are listener ages in years and genders, as well as PTAs (in dB HL based on thresholds at 0.5, 1, and 2 kHz and pooled across ears). Listeners are numbered and arranged according to increasing PTA.

Image of FIG. 4.
FIG. 4.

Mean HINT sentence component-word recognition scores for each listener. Normal-hearing listeners are represented by open symbols and hearing-impaired listeners are represented by filled symbols. Unprocessed conditions are represented by circles, and algorithm-processed conditions are represented by triangles. The upper panels display recognition in speech-shaped noise at three SNRs indicated, and the lower panels display recognition in multi-talker babble at three SNRs. The hearing-impaired listeners are numbered and plotted in order of increasing pure-tone average.

Image of FIG. 5.
FIG. 5.

Group mean component-word recognition scores and standard errors for HINT sentences presented in speech-shaped noise (upper panels) and multi-talker babble (lower panels), at the SNRs indicated, for normal-hearing and hearing-impaired listeners, both prior to and following algorithm processing.


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752b84549af89a08dbdd7fdb8b9568b5 journal.articlezxybnytfddd
Scitation: An algorithm to improve speech recognition in noise for hearing-impaired listeners